Forecasting Altcoin "Daily Price Change" Winners and Losers

[todamoon]

Your model does seem to work.
A site sounds interesting, I will keep checking back here for updates.
Keep up the good work!

[Xardas2014]

One thing seemingly overlooked, yet rather important: By posting your predictions on a public forum the prices can be influenced by that alone. I suggest you get some trusted community testers, keep it all private, analyze your formulas performance and adjust it, then post or sell the formula....which could be verified by the trusted community testers.

By simply posting the info as you are now, it is not really different from a P&D.

[jamieb81]

I like your work, I'll be watching

[gustav]

can op show us the formula?

This could also be the most sophisticated scam we will ever get to see. Imagine the guy tells you 'i am doing it based on past data' while he is actually buying and selling himself on exchange to make the thing fit. After gaining fellows like any other guru he could then command his own pumper and dumper army ... just a thought. Or why is the mathguy hanging out in this forum but is not brave enough to invest only 5$ but on the other hand has a lot of time for threads and is well educated about alts. Sorry op, didn't want to piss off, but i am overly sceptical i think - i got my reasons.

Formula or it didn't happen

I can also give out predictions and then go on exchange and make it happen. Maybe wolong/fontas just got mathematical

[Hollowman338]

definitely missed the boat on the blackcoin shenanigans.

I went ahead and dubbed these "Aurora-pumps"

[bitinlet]

Gustav and Xardas,

I understand your point of view and I think it actually makes sense. In a sense, anyone who publicly picks stocks can alter preferences, and due to that, could potentially increase demand/prices of recommended stocks. The point is valid. That said, the formula should be altered repetitively (and regressions rerun repetitively) in order to adjust for new historical data. If I do post the regression results, it will be in an academic journal.

But, getting back to posting results and boosting demand, I suppose that's an additional reason why this "could" work. But, what I was aiming to do was really test the theory here. Nothing more. I wasn't willing to toss too much money into this, and as the guy who created the model saying that I wouldn't bet on it (yet),... it would be crazy to invest your own money. Thus far, some days have worked, others not so much. But, on net, I think it's working to a degree, as winners are up. To give a bit of insight, I feel my formula is pretty much based on economic theory and swings. When I say swings, I mean it's not surprising that stocks (or in this case altcoins) that have huge swings would revert back to a mean. Since, it's a panel regression model, this is particularly true because we can measure "relative" swings from coin vs coin in variables. I use the variables on coinmarketcap.com to construct the model.

Like I've said, I'd love to figure out how to run the model consistently and do it in an easier fashion. Meaning, I'm a statistics/econ guy, not a programmer. The regressions are easy. But, I'm manually pulling the data off coinmarketcap.com. Then, I'm adjusting the data, which is labor intensive. Then, I'm plugging in the forecasted model to create a price change for each coin. The process is a pain in the ass and it's becoming more complicated as new coins enter the market. This is one reason I haven't been able to really keep up with it as much as I would have liked.

Ideally, I'd be the regression guy. That's it. That's where my experience comes from. The data pulling, the programming, etc... I'm not efficient with that. There's probably a way to do this in an easy manner if the community really wanted to get behind it. I mean, the truth is it could be automated. But, who knows if that will ever happen. Time will tell there.

[bitinlet]

Here's the model's picks for today and thier price at the time the model was ran:

Losers   
QQCoin   0.003
QubitCoin   0.00043
Premine   0.076
Phoenixcoin   0.0018
ProsperCoin   0.028
   
   
   
   
   
Winners   
Pxlcoin   0.014
FlappyCoin   0.0000062
Primecoin   1.22
Quark           0.03
RedCoin   0.0046

[todamoon]

Gustav and Xardas,

I understand your point of view and I think it actually makes sense. In a sense, anyone who publicly picks stocks can alter preferences, and due to that, could potentially increase demand/prices of recommended stocks. The point is valid. That said, the formula should be altered repetitively (and regressions rerun repetitively) in order to adjust for new historical data. If I do post the regression results, it will be in an academic journal.

But, getting back to posting results and boosting demand, I suppose that's an additional reason why this "could" work. But, what I was aiming to do was really test the theory here. Nothing more. I wasn't willing to toss too much money into this, and as the guy who created the model saying that I wouldn't bet on it (yet),... it would be crazy to invest your own money. Thus far, some days have worked, others not so much. But, on net, I think it's working to a degree, as winners are up. To give a bit of insight, I feel my formula is pretty much based on economic theory and swings. When I say swings, I mean it's not surprising that stocks (or in this case altcoins) that have huge swings would revert back to a mean. Since, it's a panel regression model, this is particularly true because we can measure "relative" swings from coin vs coin in variables. I use the variables on coinmarketcap.com to construct the model.

Like I've said, I'd love to figure out how to run the model consistently and do it in an easier fashion. Meaning, I'm a statistics/econ guy, not a programmer. The regressions are easy. But, I'm manually pulling the data off coinmarketcap.com. Then, I'm adjusting the data, which is labor intensive. Then, I'm plugging in the forecasted model to create a price change for each coin. The process is a pain in the ass and it's becoming more complicated as new coins enter the market. This is one reason I haven't been able to really keep up with it as much as I would have liked.

Ideally, I'd be the regression guy. That's it. That's where my experience comes from. The data pulling, the programming, etc... I'm not efficient with that. There's probably a way to do this in an easy manner if the community really wanted to get behind it. I mean, the truth is it could be automated. But, who knows if that will ever happen. Time will tell there.

Like you I don't know much when it comes to programming etc.
I am aware that you can get excel to auto pull data using macros. I don't know how to do this though, might be worth looking in to.

[gustav]

Gustav and Xardas,

I understand your point of view and I think it actually makes sense. In a sense, anyone who publicly picks stocks can alter preferences, and due to that, could potentially increase demand/prices of recommended stocks. The point is valid. That said, the formula should be altered repetitively (and regressions rerun repetitively) in order to adjust for new historical data. If I do post the regression results, it will be in an academic journal.

But, getting back to posting results and boosting demand, I suppose that's an additional reason why this "could" work. But, what I was aiming to do was really test the theory here. Nothing more. I wasn't willing to toss too much money into this, and as the guy who created the model saying that I wouldn't bet on it (yet),... it would be crazy to invest your own money. Thus far, some days have worked, others not so much. But, on net, I think it's working to a degree, as winners are up. To give a bit of insight, I feel my formula is pretty much based on economic theory and swings. When I say swings, I mean it's not surprising that stocks (or in this case altcoins) that have huge swings would revert back to a mean. Since, it's a panel regression model, this is particularly true because we can measure "relative" swings from coin vs coin in variables. I use the variables on coinmarketcap.com to construct the model.

Like I've said, I'd love to figure out how to run the model consistently and do it in an easier fashion. Meaning, I'm a statistics/econ guy, not a programmer. The regressions are easy. But, I'm manually pulling the data off coinmarketcap.com. Then, I'm adjusting the data, which is labor intensive. Then, I'm plugging in the forecasted model to create a price change for each coin. The process is a pain in the ass and it's becoming more complicated as new coins enter the market. This is one reason I haven't been able to really keep up with it as much as I would have liked.

Ideally, I'd be the regression guy. That's it. That's where my experience comes from. The data pulling, the programming, etc... I'm not efficient with that. There's probably a way to do this in an easy manner if the community really wanted to get behind it. I mean, the truth is it could be automated. But, who knows if that will ever happen. Time will tell there.

please link us the articel here as soon as it is published. Since i think pricechange depends on a lot of factors of which not every one is a quantitative one. Since prices are multicausal the formula should become better the more influences are captchered in it. For example: Buy/sell depth on the books and how exactly it is distributed and changes is one thing. History data is another thing, then the overall mood of the market, then the blockrewarddecrease, then the change in networkhashrate and other thing. Then when you got it running and are giving out predictions regularly and gain attention you would have to factor in also the influence of your predictions (maybe deriven from views per day of your website) - there is many factors to consider. If you can catch the bigger picture it should be possible to get something useful from it. I will be watching this thread and waiting for the published first formula. Good luck with this.

[bitinlet]

Gustav and Xardas,

I understand your point of view and I think it actually makes sense. In a sense, anyone who publicly picks stocks can alter preferences, and due to that, could potentially increase demand/prices of recommended stocks. The point is valid. That said, the formula should be altered repetitively (and regressions rerun repetitively) in order to adjust for new historical data. If I do post the regression results, it will be in an academic journal.

But, getting back to posting results and boosting demand, I suppose that's an additional reason why this "could" work. But, what I was aiming to do was really test the theory here. Nothing more. I wasn't willing to toss too much money into this, and as the guy who created the model saying that I wouldn't bet on it (yet),... it would be crazy to invest your own money. Thus far, some days have worked, others not so much. But, on net, I think it's working to a degree, as winners are up. To give a bit of insight, I feel my formula is pretty much based on economic theory and swings. When I say swings, I mean it's not surprising that stocks (or in this case altcoins) that have huge swings would revert back to a mean. Since, it's a panel regression model, this is particularly true because we can measure "relative" swings from coin vs coin in variables. I use the variables on coinmarketcap.com to construct the model.

Like I've said, I'd love to figure out how to run the model consistently and do it in an easier fashion. Meaning, I'm a statistics/econ guy, not a programmer. The regressions are easy. But, I'm manually pulling the data off coinmarketcap.com. Then, I'm adjusting the data, which is labor intensive. Then, I'm plugging in the forecasted model to create a price change for each coin. The process is a pain in the ass and it's becoming more complicated as new coins enter the market. This is one reason I haven't been able to really keep up with it as much as I would have liked.

Ideally, I'd be the regression guy. That's it. That's where my experience comes from. The data pulling, the programming, etc... I'm not efficient with that. There's probably a way to do this in an easy manner if the community really wanted to get behind it. I mean, the truth is it could be automated. But, who knows if that will ever happen. Time will tell there.

please link us the articel here as soon as it is published. Since i think pricechange depends on a lot of factors of which not every one is a quantitative one. Since prices are multicausal the formula should become better the more influences are captchered in it. For example: Buy/sell depth on the books and how exactly it is distributed and changes is one thing. History data is another thing, then the overall mood of the market, then the blockrewarddecrease, then the change in networkhashrate and other thing. Then when you got it running and are giving out predictions regularly and gain attention you would have to factor in also the influence of your predictions (maybe deriven from views per day of your website) - there is many factors to consider. If you can catch the bigger picture it should be possible to get something useful from it. I will be watching this thread and waiting for the published first formula. Good luck with this.

Agree 100%. The price change probably depends on a good amount of factors. Unfortunately, all possible variables aren't available in one location where I can pull all the data for each of the 100+ coins and analyze it across all cryptocurrencies. Given time, I think this may be possible though. For now, we can try to improve the model and see what is working and what is not. Ideally, we'd get decent results with what we do have, which could only be improved upon once more data becomes more easily accessible or available.
 

[gustav]

Gustav and Xardas,

I understand your point of view and I think it actually makes sense. In a sense, anyone who publicly picks stocks can alter preferences, and due to that, could potentially increase demand/prices of recommended stocks. The point is valid. That said, the formula should be altered repetitively (and regressions rerun repetitively) in order to adjust for new historical data. If I do post the regression results, it will be in an academic journal.

But, getting back to posting results and boosting demand, I suppose that's an additional reason why this "could" work. But, what I was aiming to do was really test the theory here. Nothing more. I wasn't willing to toss too much money into this, and as the guy who created the model saying that I wouldn't bet on it (yet),... it would be crazy to invest your own money. Thus far, some days have worked, others not so much. But, on net, I think it's working to a degree, as winners are up. To give a bit of insight, I feel my formula is pretty much based on economic theory and swings. When I say swings, I mean it's not surprising that stocks (or in this case altcoins) that have huge swings would revert back to a mean. Since, it's a panel regression model, this is particularly true because we can measure "relative" swings from coin vs coin in variables. I use the variables on coinmarketcap.com to construct the model.

Like I've said, I'd love to figure out how to run the model consistently and do it in an easier fashion. Meaning, I'm a statistics/econ guy, not a programmer. The regressions are easy. But, I'm manually pulling the data off coinmarketcap.com. Then, I'm adjusting the data, which is labor intensive. Then, I'm plugging in the forecasted model to create a price change for each coin. The process is a pain in the ass and it's becoming more complicated as new coins enter the market. This is one reason I haven't been able to really keep up with it as much as I would have liked.

Ideally, I'd be the regression guy. That's it. That's where my experience comes from. The data pulling, the programming, etc... I'm not efficient with that. There's probably a way to do this in an easy manner if the community really wanted to get behind it. I mean, the truth is it could be automated. But, who knows if that will ever happen. Time will tell there.

please link us the articel here as soon as it is published. Since i think pricechange depends on a lot of factors of which not every one is a quantitative one. Since prices are multicausal the formula should become better the more influences are captchered in it. For example: Buy/sell depth on the books and how exactly it is distributed and changes is one thing. History data is another thing, then the overall mood of the market, then the blockrewarddecrease, then the change in networkhashrate and other thing. Then when you got it running and are giving out predictions regularly and gain attention you would have to factor in also the influence of your predictions (maybe deriven from views per day of your website) - there is many factors to consider. If you can catch the bigger picture it should be possible to get something useful from it. I will be watching this thread and waiting for the published first formula. Good luck with this.

Agree 100%. The price change probably depends on a good amount of factors. Unfortunately, all possible variables aren't available in one location where I can pull all the data for each of the 100+ coins and analyze it across all cryptocurrencies. Given time, I think this may be possible though. For now, we can try to improve the model and see what is working and what is not. Ideally, we'd get decent results with what we do have, which could only be improved upon once more data becomes more easily accessible or available.
 

i guess you could also pull your data directly from first sources instead of using coinmarketcap.com
Why not use exchange-api and pull data of networks directly from the walletclients (should be possible - i don't know exactly how though. You'd need some expert on this who can tell you how to pull data from first sources). All the data can be accessed already in realtime with highest accuracy. coinmarketcap.com is a mix of data from differet exchanges. Other pages calculate slightly different numbers.  I am not an expert on the technical side. You'd need possibly someone who can tell you how to pull in the most accurate data in realtime. It is possible. That will be a some effort though to set that up for each coin. I'd recommend you look for a technical expert who can tell you where to get your desired data from in the most convinient way. Data is there already - you only need to know how to access.



Someone help this guy to get him accurate realtime data!

[jamieb81]

Keep up the good work, this is something that can get big!

[El Dude]

winners

litecoin

losers

every other coin

[barbaricmustard]

winners

litecoin

losers

every other coin

A bit closed-minded, don't you think?

[bitinlet]

Yesterday's results were OK, nothing great:

Losers   Price Yesterday   Price Today             Change
QQCoin   0.003                   0.0024           -20.00%
QubitCoin   0.00043           0.00038           -11.63%
Premine   0.076                   0.068                   -10.53%
Phoenixcoin   0.0018           0.0016           -11.11%
ProsperCoin   0.028                   0.027                    -3.57%
AVERAGE                                        -11.37%
         
         
         
         
Winners   Price Yesterday   Price Today                Change
Pxlcoin   0.014                     0.013               -7.14%
FlappyCoin   0.0000062             0.000006               -3.23%
Primecoin   1.22                     1.21                       -0.82%
Quark           0.03                     0.035               16.67%
RedCoin   0.0046             0.0048                4.35%
AVERAGE                                              +1.97%


Bitcoin       621.54                   616.61                     -.79%

[bitinlet]

Little late today, but just ran the model here are the picks (should be interesting, the model picks Aurora as a daily loser. I know that airdrop date is upcoming, so let's see what happens with that one:



Losers   Price
Animecoin   0.000018
Auroracoin   18.23
Elacoin   0.18
Bitgem   2.51
BlackCoin   0.016

   
   
   
Winners   Price
Blakecoin   0.013
ContinuumCoin   0.0000032
CasinoCoin   0.0017
BatCoin   0.000006
ZenithCoin   0.0013
   

[bitinlet]

Not good results yesterday, but if it's a caveat, I noticed I made an error in data entry, which could have thrown off the model. Here's the results:

Losers   Price Yesterday   Price Today     Change
Animecoin   0.000018          0.0000061   -66.11%
Auroracoin   18.23                  16.07           -11.85%
Elacoin   0.18                  0.14            -22.22%
Bitgem   2.51                  2.45            -2.39%
BlackCoin   0.016                  0.023            43.75%
AVERAGE                                 -11.76%

Winners   Price Yesterday   Price Today       Change
Blakecoin   0.013                   0.013                0.00%
ContinuumCoin   0.0000032   0.0000026        -18.75%
CasinoCoin   0.0017           0.0018         5.88%
BatCoin   0.000006           0.0000058        -3.33%
ZenithCoin   0.0013           0.0013         0.00%
AVERAGE                                     -3.24%
         
         
Bitcoin   612.95           607.25        -0.93%

[bitinlet]

Here's today's picks:

Losers   Price Today
66 Coin   1154
ProsperCoin   0.045
Extremecoin   0.069
BlackCoin   0.023
Pesetacoin   0.021
   
   
   
   
   
Winners   Price Today
Pandacoin (PND)   0.00000068
Premine   0.019
iCoin   0.0026
Coino   0.0023
Animecoin   0.0000061

   
   
Bitcoin   607.25

[bitinlet]

I checked the model's results earlier today. Yesterday's picks did quite well. Here were the results:

Losers   Change
66 Coin   -47.5485268630849%
ProsperCoin   0%
Extremecoin   -1.44927536231885%
BlackCoin   -17.3913043478261%
Pesetacoin   0%
AVERAGE   -13.277821314646%
   
   
   
   
Winners   Change
Pandacoin (PND)   -1.4705882352941%
Premine   26.3157894736842%
iCoin   30.7692307692308%
Coino   -34.7826086956522%
Animecoin   96.7213114754098%
AVERAGE   23.5106269574757%
   
   
Bitcoin   -1.79662412515438%
   
   
   
   
   
   

   
   
   

[bitinlet]

Here's today's picks:

Losers   Price
Animecoin   0.0000059
LottoCoin   0.000018
CorgiCoin   0.0000014
iCoin   0.0036
Murraycoin   0.0049
   
   
   
   
Winners   Price
ContinuumCoin   0.0000038
Grain   0.0000059
66 Coin   1719
CacheCoin   1.43
ORObit   0.0035

   
   
Bitcoin   592.13